This repository serves as a crash course designed for undergraduates joining CoCo lab (Or any interested student if they find it helpful). The aim is to help them familiarize themselves with the tools and technologies commonly used in the lab. The course includes the following topics:
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Introduction to Git (module 1): Learn the basics of version control with Git. Link
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Introduction to Python (module 2): Get started with Python programming, covering fundamental concepts and syntax ranging from python installation to different libraries and the use of VSCode and jupyter notebooks. Link
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Getting Started with Python-MNE (module 3): Explore the basics of working with Python-MNE for magnetoencephalography (MEG) and electroencephalography (EEG) data. Link
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Introduction to Alliance Canada (module 4): Understand the basics of accessing and utilizing resources on Alliance Canada. Link
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Getting Started with Scikit-learn (module 5): Learn the fundamentals of machine learning using Scikit-learn in Python and how to apply it for neuroscience. Link
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Introduction to Source Estimation (module 6): Explore the concepts and usage of source estimation in Python. Link
Feel free to explore each module to access specific learning materials and resources. Follow the README files in each module for detailed instructions and guidance related to the respective topic. This crash course aims to provide a solid foundation for undergraduates entering CoCoLab, helping them navigate the tools and technologies essential for their work.
For more detailed notebooks on working with brain data, we highly recommend checking out the PSY2007D course materials. The notebooks numbered 0 to 8 in the main folder provide comprehensive guides and exercises.
To get started with the crash course, you'll need to set up your Python environment. We recommend using a virtual environment.
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Clone the repository:
git clone https://github.com/thecocolab/crashcourse.git cd crashcourse -
Create and activate a virtual environment:
python -m venv venv source venv/bin/activate # On Windows use: venv\Scripts\activate
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Install dependencies:
pip install -r requirements.txt